• Title/Summary/Keyword: Accuracy assessment of data

Search Result 667, Processing Time 0.037 seconds

Nondestructive Quantification of Corrosion in Cu Interconnects Using Smith Charts (스미스 차트를 이용한 구리 인터커텍트의 비파괴적 부식도 평가)

  • Minkyu Kang;Namgyeong Kim;Hyunwoo Nam;Tae Yeob Kang
    • Journal of the Microelectronics and Packaging Society
    • /
    • v.31 no.2
    • /
    • pp.28-35
    • /
    • 2024
  • Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

Comparative assessment and uncertainty analysis of ensemble-based hydrologic data assimilation using airGRdatassim (airGRdatassim을 이용한 앙상블 기반 수문자료동화 기법의 비교 및 불확실성 평가)

  • Lee, Garim;Lee, Songhee;Kim, Bomi;Woo, Dong Kook;Noh, Seong Jin
    • Journal of Korea Water Resources Association
    • /
    • v.55 no.10
    • /
    • pp.761-774
    • /
    • 2022
  • Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

Evaluation of SATEEC Daily R Module using Daily Rainfall (일강우를 고려한 SATEEC R 모듈 적용성 평가)

  • Woo, Wonhee;Moon, Jongpil;Kim, Nam Won;Choi, Jaewan;Kim, Ki-sung;Park, Youn Shik;Jang, Won Seok;Lim, Kyoung Jae
    • Journal of Korean Society on Water Environment
    • /
    • v.26 no.5
    • /
    • pp.841-849
    • /
    • 2010
  • Soil erosion is an natural phenomenon. However accelerated soil erosion has caused many environmental problems. To reduce soil loss from a watershed, many management practices have been proposed worldwide. To develop proper and efficient soil erosion best management practices, soil erosion rates should be estimated spatially and temporarily. The Universal Soil Loss Equation (USLE) and USLE-based soil erosion and sediment modelling systems have been developed and tested in many countries. The Sediment Assessment Tool for Effective Erosion Control (SATEEC) system has been developed and enhanced to provide ease-of-use interface to the USLE users. However many researchers and decision makers have requested to enhance the SATEEC system for simulation of soil erosion and sediment reflecting effects of single storm event. Thus, the SATEEC R factors were estimated based on 5 day antecedent rainfall data. The SATEEC 2.1 daily R factor was applied to the study watershed and it was found that the R2 and EI values (0.776 and 0.776 for calibration and 0.927 and 0.911 for validation) with the daily R were greater than those (0.721 and 0.720 for calibration and 0.906 and 0.881 for validation) with monthly R, which was available in the SATEEC 2.0 system. As shown in this study, the SATEEC with daily R can be used to estimate soil erosion and sediment yield at a watershed scale with higher accuracy. Thus the SATEEC with daily R can be efficiently used to develop site-specific soil erosion best management practices based on spatial and temporal analysis of soil erosion and sediment yield at a daily-time step, which was not possible with USLE-based soil erosion modeling system.

Riparian Connectivity Assessment Using Species Distribution Model of Fish Assembly (어류군집의 종분포모형을 이용한 수변지역 연결성 평가)

  • Jeong, Seung Gyu;Lee, Dong Kun;Ryu, Ji Eun
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.23 no.2
    • /
    • pp.17-26
    • /
    • 2015
  • River corridors facilitate dispersal and movement and prevent local extinction of species. As a result of stream restoration projects, which include installation of waterfront and flood control structures, the number of animals, which rely on river corridor, is decreasing. For the study, factors affecting fish assembly were extracted by a species distribution model with the fish data collected from the Seom River in Hoengseong County and City of Wonju, Ganwon Province, Korea between March to October 2013. The riparian connectivity was assessed using species richness and rarity. According to result of the field survey, there were 38 species and 7,061 individuals for fish. The analysis suggests the following. Firstly, factors affecting fish richness in species distribution model results are shown to be velocity, riffle, riparian width, and water width. The accuracy of the model proves to be suitable with the correlation coefficient of 0.83 and MAPE of 19.2%. Secondly, the low rarity area is shown to be straight streams in Jeon river near to Hongseong County and the high rarity area to be streams with large width, existing alluvial area at channel junction between Jeon river and Seom river. Thirdly, according to connectivity results, areas where weirs are installed or riparian buffer area is removed showed low connectivity. The areas where farmland near riparian and forest areas showed high connectivity. The results of this study can be utilized to improve current facilities and enhance connectivity as a restoration guide.

Quality Assurance of Multileaf Collimator Using Electronic Portal Imaging (전자포탈영상을 이용한 다엽시준기의 정도관리)

  • ;Jason W Sohn
    • Progress in Medical Physics
    • /
    • v.14 no.3
    • /
    • pp.151-160
    • /
    • 2003
  • The application of more complex radiotherapy techniques using multileaf collimation (MLC), such as 3D conformal radiation therapy and intensity-modulated radiation therapy (IMRT), has increased the significance of verifying leaf position and motion. Due to thier reliability and empirical robustness, quality assurance (QA) of MLC. However easy use and the ability to provide digital data of electronic portal imaging devices (EPIDs) have attracted attention to portal films as an alternatives to films for routine qualify assurance, despite concerns about their clinical feasibility, efficacy, and the cost to benefit ratio. In this study, we developed method for daily QA of MLC using electronic portal images (EPIs). EPID availability for routine QA was verified by comparing of the portal films, which were simultaneously obtained when radiation was delivered and known prescription input to MLC controller. Specially designed two-test patterns of dynamic MLC were applied for image acquisition. Quantitative off-line analysis using an edge detection algorithm enhanced the verification procedure as well as on-line qualitative visual assessment. In conclusion, the availability of EPI was enough for daily QA of MLC leaf position with the accuracy of portal films.

  • PDF

Assessing Distress Prediction Model toward Jeju District Hotels (제주지역 호텔기업 부실예측모형 평가)

  • Kim, Si-Joong
    • The Journal of Industrial Distribution & Business
    • /
    • v.8 no.4
    • /
    • pp.47-52
    • /
    • 2017
  • Purpose - This current study will investigate the average financial ratio of top and failed five-star hotels in the Jeju area. A total of 14 financial ratio variables are utilized. This study aims to; first, assess financial ratio of the first-class hotels in Jeju to establishing variables, second, develop distress prediction model for the first-class hotels in Jeju district by using logit analysis and third, evaluate distress prediction capacity for the first-class hotels in Jeju district by using logit analysis. Research design, data, and methodology - The sample was collected from year 2015 and 14 financial ratios of 12 first-class hotels in Jeju district. The results from the samples were analyzed by t-test, and the independent variables were chosen. This was an empirical study where the distress prediction model was evaluated by logit analysis. This current research has focused on critically analyzing and differentiating between the top and failed hotels in the Jeju area by utilizing the 14 financial ratio variables. Results - The verification result of the accuracy estimated by logit analysis has shown to indicate that the distress prediction model's distress prediction capacity was 83.3%. In order to extract the factors that differentiated the top hotels in the Jeju area from the failed hotels among the 14 chosen, the analysis of t-black was utilized by independent variables. Logit analysis was also used in this study. As a result, it was observed that 5 variables were statistically significant and are included in the logit analysis for discernment of top and failed hotels in the Jeju area. Conclusions - The distress prediction press' prediction capability was compared in this research analysis. The distress prediction press prediction capability was shown to range from 75-85% by logit analysis from a previous study. In this current research, the study's prediction capacity was shown to be 83.33%. It was considered a high number and was found to belong to the range of the previous study's prediction capacity range. From a practical perspective, the capacity of the assessment of the distress prediction model in the top and failed hotels in the Jeju area was considered to be a prominent factor in applications of future hotel appraisal.

Prediction of Water Storage Rate for Agricultural Reservoirs Using Univariate and Multivariate LSTM Models (단변량 및 다변량 LSTM을 이용한 농업용 저수지의 저수율 예측)

  • Sunguk Joh;Yangwon Lee
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.5_4
    • /
    • pp.1125-1134
    • /
    • 2023
  • Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.

A Prediction Method of the Gas Pipeline Failure Using In-line Inspection and Corrosion Defect Clustering (In-line Inspection과 부식결함 클러스터링을 이용한 가스배관의 고장예측)

  • Kim, Seong-Jun;Choe, Byung Hak;Kim, Woosik
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.24 no.6
    • /
    • pp.651-656
    • /
    • 2014
  • Corrosion has a significant influence upon the reliability assessment and the maintenance planning of gas pipeline. Corrosion defects occurred on the underground pipeline can be obtained by conducting periodic in-line inspection (ILI). However, little study has been done for practical use of ILI data. This paper deals with remaining lifetime prediction of the gas pipeline in the presence of corrosion defects. Because a pipeline parameter includes uncertainty in its operation, a probabilistic approach is adopted in this paper. A pipeline fails when its operating pressure is larger than the pipe failure pressure. In order to estimate the failure probability, this paper uses First Order Reliability Method (FORM) which is popular in the field of structural engineering. A well-known Battelle code is chosen as the computational model for the pipe failure pressure. This paper develops a Matlab GUI for illustrating failure probability predictions Our result indicates that clustering of corrosion defects is helpful for improving a prediction accuracy and preventing an unnecessary maintenance.

Assessment of Dosimetric Leaf Gap According to Measuring Active Volume of Detector (검출기 측정 용적에 따른 Dosimetric Leaf Gap 변화와 정확성 검증에 대한 연구)

  • Dae-Hyun, Kim
    • Journal of the Korean Society of Radiology
    • /
    • v.16 no.7
    • /
    • pp.863-870
    • /
    • 2022
  • DLG (Dosimetric Leaf Gap) and transmission factor are important parameters of MLC modeling in treatment planning system. In this study, DLG and transmission factor of HD-MLC were measured using detector with different measuring volumes, and the accuracy of the treatment plans was evaluated according to the DLG values. DLG was measured using the dynamic sweeping gap method with Semiflux3D and MicroDiamond detectors. Then, 10 radiation treatment plans were generated to optimize the DLG value and compared with the measurement results. Photon energies 6, 8, 10 MV, the DLG measured by Semiflux3D were 0.76, 0.83, and 0.85 mm, and DLG measured by MicroDiamond were 0.78, 0.86, and 0.9 mm. All plans were measured by portal dosimetry and analyzed using Gamma Evaluation. In the 6 MV photon beams, the average gamma passing rate were 94.3% and 98.4% for DLG 0.78 mm and 1.15 mm. In the 10 MV photon beam, the average gamma passing rate were 91.2% and 97.6% for DLG 0.9 mm and 1.25 mm. HD-MLC needs accurate modeling in the treatment planning system. DLG could be used measured data using small volume detector. However, for better radiation therapy, DLG should be optimized at the commissioning stage of LINAC.

Validation of a trienzyme-Lactobacillus casei method for folate analysis in fishery resources consumed in the Korean diet (Trienzyme과 Lactobacillus casei를 이용한 국내 수산 자원의 엽산 분석 및 유효성 검증)

  • Jeong, Bomi;Nam, Ki-Ho;Kim, Yeon-Kye;Chun, Jiyeon
    • Korean Journal of Food Science and Technology
    • /
    • v.52 no.6
    • /
    • pp.580-586
    • /
    • 2020
  • Fishery resources have been widely consumed as protein- and vitamin-rich food sources in the Korean diet. However, information regarding their vitamin levels is extremely limited. In this study, trienzyme-Lactobacillus casei method was validated and used to determine the folate contents in fishery foods. The trienzyme-L. casei method for folate analysis showed excellent accuracy (85.2 to 95.3% recovery) and precision (repeatability 1.4% RSD and reproducibility 2.4% RSD). Folate contents of 20 fish foods (4 fish, 3 crustaceans, 3 sea algae, 3 cephalopods, 4 shellfish, and 3 others) ranged from 1.75 to 97.98 ㎍/100 g. Furthermore, we found that the folate content in seaweed fusiforme was the highest, followed by gulfweed (69.73 ㎍/100 g). Folate analysis using the trienzyme-L. casei method was determined excellent based on the z-score of -0.3 in the Food Analysis Performance Assessment Scheme test. Analytical and method validation data generated in this study could be used to update the national food composition table on vitamin B9 in Korean fishery resources.